摘要
为了使“区间”形式加以表述的不确定信息的提取具有侧重性,需提取出对象(属性)集对应的属性(对象)区间集。本文在模糊形式背景中,通过引入2个阈值,将单边区间集与经典半概念结合,提取出属性(对象)集对应的对象(属性)区间集,从而提出区间集外延–集合内涵(集合外延–区间集内涵)(interval set extent-set intent(set extent-interval set intent),ISE-SI(SE-ISI))型单边区间集模糊半概念。全体ISE-SI(SE-ISI)型单边区间集模糊半概念构成格,并给出基于格搜寻全体ISE-SI(SE-ISI)型单边区间集模糊半概念的算法。通过与已有成果对比,显示出这2种知识表示形式的多方优势。本文所得结果在知识表示及提取方法上具有适用范围广、实际应用强等优点。
To ensure that the extraction of uncertain information expressed in the form of"intervals"is focused,it is necessary to extract the corresponding attribute(object)interval set for the object(attribute)set.By introducing two thresholds from the fuzzy context,the unilateral interval set is combined with the classical semiconcept to extract the corresponding object(attribute)interval set for the attribute(object)set,and thereby the interval set extent-set intent(set extent-interval set intent)(ISE-SI(SE-ISI))type partially-known fuzzy semiconcept is proposed.All ISE-SI(SE-ISI)type partially-known fuzzy semiconcepts form a lattice,and the algorithm based on lattice search for all ISE-SI(SE-ISI)type partially-known fuzzy semiconcepts is given.The multiple advantages of these two knowledge representation forms are demonstrated by comparing them with existing achievements.The results obtained in this paper have the advantages of broad applicability and strong practical application in knowledge representation and extraction methods.
作者
毛华
胥德华
刘川
郑博雅
王刚
张植明
MAO Hua;XU Dehua;LIU Chuan;ZHENG Boya;WANG Gang;ZHANG Zhiming(College of Mathematics and Information Science,Hebei University,Baoding 071002,China;Hebei Key Laboratory of Machine Learning and Computational Intelligence,Hebei University,Baoding 071002,China;College of Life Science,Hebei University,Baoding 071002,China)
出处
《智能系统学报》
CSCD
北大核心
2024年第4期1016-1026,共11页
CAAI Transactions on Intelligent Systems
基金
国家自然科学基金项目(61572011)
河北省高等学校人文社会科学研究项目(SZ2023135).
关键词
模糊形式背景
半概念
区间集
区间集概念
单边区间集概念
模糊概念
单边区间集模糊半概念
知识表示和提取
fuzzy formal context
semiconcept
interval set
interval-set concept
partially-known formal concept
fuzzy concept
partially-known fuzzy semiconcept
knowledge representation and extraction
